A neural network based computational model to predict the output power of different types of photovoltaic cells.
In this article, we introduced an artificial neural network (ANN) based computational model to predict the output power of three types of photovoltaic cells, mono-crystalline (mono-), multi-crystalline (multi-), and amorphous (amor-) crystalline. The prediction results are very close to the experime...
Main Authors: | WenBo Xiao, Gina Nazario, HuaMing Wu, HuaMing Zhang, Feng Cheng |
---|---|
Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS)
2017-01-01
|
Series: | PLoS ONE |
Online Access: | http://europepmc.org/articles/PMC5595326?pdf=render |
Similar Items
-
Modelling and Prediction of Photovoltaic Power Output Using Artificial Neural Networks
by: Aminmohammad Saberian, et al.
Published: (2014-01-01) -
Improved Probability Prediction Method Research for Photovoltaic Power Output
by: Ze Cheng, et al.
Published: (2019-05-01) -
Improved artificial neural network method for predicting photovoltaic output performance
by: Siyi Wang, et al.
Published: (2020-12-01) -
Recurrent Neural Network-Based Hourly Prediction of Photovoltaic Power Output Using Meteorological Information
by: Donghun Lee, et al.
Published: (2019-01-01) -
Prediction in Photovoltaic Power by Neural Networks
by: Antonello Rosato, et al.
Published: (2017-07-01)